Designing Context-Based Marketing: Product Recommendations Under Time Pressure

We study how to design product recommendations when consumers’ attention and utility are influenced by time pressure—a prominent example of the context effect—and menu characteristics, such as the number of recommended products in the assortment. Using unique data on consumer purchases from vending machines on train platforms in Tokyo, we develop and estimate a structural consideration set model in which time pressure and recommendations can influence attention and utility. We find that time pressure reduces consumer attention but increases utility. Time pressure moderates the effect of recommendations for the attention of both recommended and nonrecommended products and utility for recommended products. Moreover, the number of total recommendations increases consumer attention in general, but in a diminishing way. In our counterfactual simulations, we find that the revenue-maximizing number of recommendations decreases with time pressure and that optimizing recommending products to accommodate time pressure by a greedy algorithm increases total sales volume by 3.7% relative to the actual policy, 0.6% points more than traditional consumer-segment-based targeting policy. This effect is larger than 10% price discounts, which increases the revenue only by 0.4% at the margin.